docstr: The common (Q-net and policy-net) forward pass.
  
  NOTE: It is not(!) recommended to override this method as it would
  introduce a shared pre-network, which would be updated by both
  actor- and critic optimizers.
  
  For rnn support remove input_dict filter and pass state and seq_lens
docstr_tok: ["The","common","(","Q-net","and","policy-net",")","forward","pass",".","NOTE",":","It","is","not","(","!",")","recommended","to","override","this","method","as","it","would","introduce","a","shared","pre-network",",","which","would","be","updated","by","both","actor-","and","critic","optimizers",".","For","rnn","support","remove","input_dict","filter","and","pass","state","and","seq_lens"]
code: def forward(
      self,
      input_dict: Dict[str, TensorType],
      state: List[TensorType],
      seq_lens: TensorType,
  ) -> (TensorType, List[TensorType]):
      """The common (Q-net and policy-net) forward pass.
  
      NOTE: It is not(!) recommended to override this method as it would
      introduce a shared pre-network, which would be updated by both
      actor- and critic optimizers.
  
      For rnn support remove input_dict filter and pass state and seq_lens
      """
      model_out = {"obs": input_dict[SampleBatch.OBS]}
  
      if self.use_prev_action:
          model_out["prev_actions"] = input_dict[
              SampleBatch.PREV_ACTIONS
          ]
      if self.use_prev_reward:
          model_out["prev_rewards"] = input_dict[
              SampleBatch.PREV_REWARDS
          ]
  
      return model_out, state
  
file_path: ray/rllib/algorithms/sac/rnnsac_torch_model.py
imports: import gymnasium
  from typing import Optional, List, Dict
  from ray.rllib.algorithms.sac.sac_torch_model import SACTorchModel
  from ray.rllib.models.modelv2 import ModelV2
  from ray.rllib.policy.sample_batch import SampleBatch
  from ray.rllib.policy.view_requirement import ViewRequirement
  from ray.rllib.utils import override, force_list
  from ray.rllib.utils.framework import try_import_torch
  from ray.rllib.utils.typing import ModelConfigDict, TensorType
label_desc: Use image node_id 2 for calling the RNNSACTorchModel obj's underlying member method code with example usage: obj.forward(input_dict, state, seq_lens) and returns: model_out,  state